By Xi Lin
Picture this: You’re in a construction estimating class, staring at a giant floor plan PDF. There are rooms within rooms, hallways branching like mazes, and four different flooring types you need to calculate and categorize. Your team is trying to divide the work, someone is wrestling with Bluebeam’s measurement tools, and someone else is triple-checking the math in Excel.
It’s slow. It’s draining. And if one person mis-clicks, the whole estimate can collapse like a house of cards.
Now imagine instead that you upload the blueprint and — boom — the software highlights, categorizes, and tallies most of the measurements for you.
That’s the promise of Togal AI, an AI-powered estimation tool that researchers Drs. Tianjiao Zhao, Xi Lin, and Ri Na studied alongside the industry-standard Bluebeam Revu 20. They explored: Can AI actually improve learning in construction education, or does it risk making students too dependent on automation?
The Problem: Estimation is Hard… and Time-Consuming
Construction estimation isn’t just typing numbers in a calculator — it’s spatial interpretation, precision, grouping, materials logic, and constant rechecking. Traditional digital tools like Bluebeam are powerful but require tons of manual clicking, adjusting, verifying, and recalculating.
And in a classroom full of students new to the process?
It’s even harder.
The Experiment: AI vs. Manual Digital Tools
Sixty undergraduate students worked in small groups to estimate the flooring for a school building:
- One set of students used Bluebeam first
- The other used Togal AI first
- Then they switched tools and compared experiences
- Surveys + task data + reflections were analyzed
The steps included:
- Interpreting the floor plan
- Dividing group roles
- Measuring four types of flooring
- Summarizing the areas
- Handling a change order scenario (a real-world curveball)
What Happened: Togal AI Changed the Game
|
Task |
Bluebeam |
Togal AI |
|
Overall Task Time |
Long |
51% faster ⏱️ |
|
Accuracy |
Good |
20% better 🎯 |
|
Confidence |
Moderate |
55% boost 💪 |
|
Change Order Task |
Slow |
76% faster 🚀 |
Students using Togal AI spent less time fighting the software and more time actually thinking about the project.
One student put it perfectly: “AI let me focus on the reasoning part instead of the clicking part.”
What Improved
✅ Efficiency: Less manual measuring → more time discussing
decisions
✅ Accuracy: AI made fewer calculation errors than students did
✅ Teamwork: Faster workflow meant smoother collaboration
✅ Confidence: Students felt more capable of handling real project
tasks
But Wait — There’s a Catch
AI didn’t replace critical thinking — but some students did lean on it too much.
A few said: “It was so fast that I stopped double-checking.”
Others worried: “If AI does all the work, how will we really learn estimating?”
And one student said the quiet part out loud: “I’m going to be an estimator — I don’t want a robot taking my job.”
This highlights a key takeaway:
AI should support, not replace, the core skill of understanding how estimates are made.
The Big Idea: Use Both, but Use Them in Order
The researchers recommend:
- Teach manual logic first (Bluebeam).
- Then introduce automation (Togal AI).
- Have students compare outputs — and explain discrepancies.
This builds:
- Procedural knowledge 🧱
- Critical verification habits 🔍
- And modern AI fluency 🤝
Final Thought: AI Isn’t Here to Replace Estimators — It’s Here to Upgrade Them
This study shows that when thoughtfully integrated, AI doesn’t make learning shallow — it frees space for deeper reasoning:
Students weren’t just measuring anymore.
They were:
- Analyzing change orders
- Discussing resource trade-offs
- Thinking like project managers
That’s not automation replacing skill. That’s an automation enabling skill.
As the authors show:
The future estimator is not the person who measures fastest — it’s the
person who knows how to verify, interpret, and make decisions with smart tools.
Reference
Zhao, T., Lin, X., & Ri, N. (2025). Integrating AI in Construction Estimation Education: A Comparative Study of Togal AI and Bluebeam Revu 20. European Journal of Education, 60(4). https://doi.org/10.1111/ejed.70287
